Security analysis and defense strategy of distributed filtering under false data injection attacks

This paper investigates the distributed state estimation for multi-sensor networks under false data injection attacks. The well-known chi(2) detector is first considered for detecting the authenticity of the transmitted data. A necessary and sufficient condition for the insecurity of the distributed estimation system is derived under which the hostile attacks can bypass the false data detector and degrade the estimation performance. Moreover, an algorithm for generating false data is provided to keep the attack stealthy. In order to overcome the detection vulnerability, a new protection strategy is proposed to ensure that the distributed estimator is secure under false data injection attacks. It is worth emphasizing that the strategy adopts a stochastic rule instead of a fixed threshold to detect suspicious data, which effectively avoids the occurrence of the truncated Gaussian distribution. A simulation example of moving vehicle is presented to demonstrate the effectiveness of the developed approaches. (C)& nbsp;2022 Elsevier Ltd. All rights reserved.

Automated summary

This paper investigates the distributed state estimation for multi-sensor networks under false data injection attacks. It first considers the chi(2) detector for detecting the authenticity of transmitted data and derives a necessary and sufficient condition for the insecurity of the distributed estimation system. It then proposes an algorithm for generating false data and a new protection strategy to ensure the security of the distributed estimator.